137 Open source projects that are alternatives of or similar to TAA-PG

I have been deeply interested in algorithmic trading and systematic trading algorithms. This Repository contains the code of what I have learnt on the way. It starts form some basic simple statistics and will lead up to complex machine learning algorithms.

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

PortfolioLab is a python library that enables traders to take advantage of the latest portfolio optimisation algorithms used by professionals in the industry.

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

This repository contains the customized trading algorithms that I have created using the Quantopian IDE.

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

Functions for the construction of risk-based portfolios

강화학습에 대한 기본적인 알고리즘 구현

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks

TensorFlow A2C to solve Acrobot, with synchronized parallel environments

Combining deep learning and reinforcement learning.

Scalable, event-driven, deep-learning-friendly backtesting library

Code for "Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner" in ICCV 2017

Monte Carlo simulation of energy-dispersive X-ray fluorescence spectrometers

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

ANTARES Visualizations

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

NCrystal : a library for thermal neutron transport in crystals and other materials

Deep reinforcement learning using baidu PARL(maze,flappy bird and so on)

📓 List of portfolio management resources, using Reinforcement Learning.

Deep Reinforcement Learning For Sequence to Sequence Models

parse-account-statements.py bereitet Kontoauszüge verschiedener bekannter P2P Kreditanbieter (wie z.B. Mintos, Estateguru, ...) in einem von PortfolioPerformance lesbaren CSV-Format auf.

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

Implementations of Reinforcement Learning Models in Tensorflow

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

A Clearer and Simpler Synchronous Advantage Actor Critic (A2C) Implementation in TensorFlow

Ranking Policy Gradient

Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

Flr(Flutter-R) Extension: A Flutter Resource Manager VSCode Extension

Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

A Power BI template that provides easy to understand, actionable flow metrics and predictive analytics for your agile teams using Azure DevOps, Azure DevOps Server and/or TFS.

Highly Modular and Scalable Reinforcement Learning

assets management tool for Flutter

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

Reinforcement learning tutorials

A course on Deep Reinforcement Learning in Computer Vision. Visit Website:

A program that implements the portfolio optimization experiments using a hybrid quantum computing algorithm from arXiv:1911.05296. The code was developed as part of the 2020 Quantum mentorship program. Many thanks to my mentor Guoming Wang from Zapata Computing!

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

Quantitative analysis, strategies and backtests

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

A Python/Vue.js crypto portfolio management and trade automation program with support for 10 exchanges.

A simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)

Solvers/annealers for simulated quantum annealing on CPU and CUDA(NVIDIA GPU).

DEEp Reinforcement learning framework

No description or website provided.

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

Minimal and Clean Reinforcement Learning Examples

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

A curated list of Monte Carlo tree search papers with implementations.

Super Mario Reinforcement Learning from Demonstration

An elegant PyTorch deep reinforcement learning library.

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

[OLD!] RGB Protocol specifications for Bitcoin-based digital assets

Cassandra is a Monte Carlo package to conduct atomistic simulations.